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ISNet: Shape Matters for Infrared Small Target Detection

CVPR 2022 · Detection and segmentation › CNN features · approach: Domain-specific segmentation and detection · 715 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use ISNet instead of ALCNetIRSTD detection · NUAA-SIRSTIoU (%): 74.31 -> 80.02Helped
Use ISNet instead of ALCNetIRSTD detection · IRSTD-1kIoU (%): 62.05 -> 68.77Helped
Add TOAA to U-Net (ablation)U-Net · NUAA-SIRSTIoU (%): 68.31 -> 75.65Helped
Add TFD-inspired edge block to U-Net (ablation)U-Net · NUAA-SIRSTIoU (%): 68.31 -> 78.05Helped
Add TOAA and TFD edge blocks to U-Net (ablation)U-Net · NUAA-SIRSTIoU (%): 68.31 -> 80.02Helped
Use TOAA rather than no TOAA blocks (ablation)ISNet · NUAA-SIRSTIoU (%): 68.31 -> 75.65Helped
Increase TOAA blocks from 2 to 3 (ablation)ISNet · NUAA-SIRSTIoU (%): 75.65 -> 75.61No clear effect
Use the TFD design rather than gated convolution only (ablation)ISNet edge block · NUAA-SIRSTIoU (%): 75.38 -> 78.05Helped
Add a bottleneck to gated convolution (ablation)ISNet edge block · NUAA-SIRSTIoU (%): 75.38 -> 76.32Helped
Add a residual block to gated convolution (ablation)ISNet edge block · NUAA-SIRSTIoU (%): 75.38 -> 77.23Helped
Use TFD edge blocks rather than none (ablation)ISNet · NUAA-SIRSTIoU (%): 68.31 -> 78.05Helped
Increase TFD edge blocks from 3 to 4 (ablation)ISNet · NUAA-SIRSTIoU (%): 78.05 -> 78.15No clear effect

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